How Can a Deep Learning Algorithm Improve Fracture Detection on X-rays in the Emergency Room?

In order to address this growing shortage of healthcare professionals and provide ever more accurate and rapid diagnoses for more precise clinical decision-making, AI solutions have emerged, particularly in medical imaging. This year, AZmed is proud to present two scientific papers at this year's congress concerning the detection of CHEST anomalies on standard radiographs.

Fracture detection solutions are particularly critical in this context, as radiographic fracture identification remains highly complex and challenging. To address this persistent issue, the National Institute for Health and Care Excellence (NICE) in the UK established a committee to assess the role of AI in radiology and shortlisted top fracture detection AI solutions, including AZmed’s AZtrauma, one of the verticals of Rayvolve® AI suite, as part of its Early Value Assessment (EVA).

AZtrauma, fully certified MDaaS software for fracture detection by AZmed, uses sophisticated algorithms to analyze and detect bone fractures, dislocations, and joint effusions in medical images. Utilizing advanced deep learning and computer vision technologies, AZtrauma significantly enhances the productivity and precision of fracture diagnosis for radiologists.